Object Segmentation

In order to grasp granular characteristics about an object, our segmentation techniques generate pixel-wise masks for each object. While semantic segmentation processes apply a label to each pixel in an image, considering multiple objects of the same class as a single entity, instance segmentation processes treat multiple objects of the same class as different individual objects (or instances).

Divide & Deduce

Divide & Deduce

Image segmentation helps divide a digital image into various segments (regions or categories) based on its attributes and features.

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The primary goal of every segmentation method is to simplify the image by precisely delineating it from within the visual data and make it more understandable and easier to examine.

Intelligent solutions around Object Segmentation

With use cases including applications like facial segmentation to determine age, gender etc. medical imaging, land use pattern understanding, traffic analysis and many more.

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The precise deduction of meaningful information from visual data makes the process immensely useful for driving intelligence in systems.

Intelligent solutions around Object Segmentation

Object Segmentation for Analyzing Exterior Scenes

Frames of the video from an exterior scene analysed in real-time by Vision AI

Object Segmentation for Analyzing Interior Scenes

Frames of the video from an interior scene analysed in real-time by Vision AI

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Transformative Applications of Computer Vision in Education

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Transformative Applications of Computer Vision in Education

We need to keep up with changing times, particularly in the field of education, where there is innovation and discovery each day. Given the advancements in artificial intelligence and its subfields, it would be a massive mistake to ignore the incredible potential these technological fields offer. Using the crucial data provided by computer vision systems, educators can design each class to be more interactive, improving students’ moods, attendance and overall grades.

A guide to computer vision platforms

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A guide to computer vision platforms

This journey from early-stage visual biometric systems to self-driving cars shows the promise the field of Computer Vision holds for the future which has constantly been seen as a highly automated one. To push this automation to the next levels, we need our machines to see, analyze and act more smartly.

Deep Learning and AI: Applications

Article

Deep Learning and AI: Applications

Computers have come a long way from being a calculator to bearing artificial intelligence capacity, giving incredible results. Sometimes, those results are better than the average human outcomes, in highly specialized situations. Recent developments and technological breakthroughs have allowed computers to develop highly optimized analytical frameworks and predict situations with high degrees of accuracy. Thus, Artificial Intelligence and technologies like Deep Learning have extensive applications in nearly all sectors. In many scenarios, these technologies are making work possible without any human intervention.

Case Studies

Sports & Player Management Case Study

Tooliqa combined knowledge about immersive experiences, IOT, and remote monitoring to develop Live Video Analytics for a football and basketball match, implementing object detection and tracking using deep learning. This was done using in-house knowledge of the sports industry and advanced technologies relevant in this case.

Sports & Player Management Case Study

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